package com.atguigu.prim;

import java.util.Arrays;

public class PrimAlgorithm {

  public static void main(String[] args) {
    //测试看看图是否创建ok
    char[] data = new char[]{'A','B','C','D','E','F','G'};
    int verxs = data.length;
    //邻接矩阵的关系使用二维数组表示,10000这个大数，表示两个点不联通
    int [][]weight=new int[][]{
        {10000,5,7,10000,10000,10000,2},
        {5,10000,10000,9,10000,10000,3},
        {7,10000,10000,10000,8,10000,10000},
        {10000,9,10000,10000,10000,4,10000},
        {10000,10000,8,10000,10000,5,4},
        {10000,10000,10000,4,5,10000,6},
        {2,3,10000,10000,4,6,10000},};

    //创建MGraph对象
    MGraph graph = new MGraph(verxs);
    //创建一个MinTree对象
    MinTree minTree = new MinTree();
    minTree.createGraph(graph, verxs, data, weight);
    //输出
    minTree.showGraph(graph);
    //测试普利姆算法
    minTree.prim(graph, 1);//
  }

}

//创建最小生成树->村庄的图
class MinTree {
  //创建图的邻接矩阵
  /**
   *
   * @param graph 图对象
   * @param verxs 图对应的顶点个数
   * @param data 图的各个顶点的值
   * @param weight 图的邻接矩阵
   */
  public void createGraph(MGraph graph, int verxs, char data[], int[][] weight) {
    int i, j;
    for(i = 0; i < verxs; i++) {//顶点
      graph.data[i] = data[i];
      for(j = 0; j < verxs; j++) {
        graph.weight[i][j] = weight[i][j];
      }
    }
  }

  //显示图的邻接矩阵
  public void showGraph(MGraph graph) {
    for(int[] link: graph.weight) {
      System.out.println(Arrays.toString(link));
    }
  }

  //编写prim算法，得到最小生成树
  /**
   *
   * @param graph 图
   * @param v 表示从图的第几个顶点开始生成'A'->0 'B'->1...
   */
  public void prim(MGraph graph, int v) {
    //visited[] 标记结点(顶点)是否被访问过
    int visited[] = new int[graph.verxs];
    //visited[] 默认元素的值都是0, 表示没有访问过
//		for(int i =0; i <graph.verxs; i++) {
//			visited[i] = 0;
//		}

    //把当前这个结点标记为已访问
    visited[v] = 1;
    //h1 和 h2 记录两个顶点的下标
    int h1 = -1;
    int h2 = -1;
    int minWeight = 10000; //将 minWeight 初始成一个大数，后面在遍历过程中，会被替换
    for(int k = 1; k < graph.verxs; k++) {//因为有 graph.verxs顶点，普利姆算法结束后，有 graph.verxs-1边

      //这个是确定每一次生成的子图 ，和哪个结点的距离最近
      for(int i = 0; i < graph.verxs; i++) {// i结点表示被访问过的结点
        for(int j = 0; j< graph.verxs;j++) {//j结点表示还没有访问过的结点
          if(visited[i] == 1 && visited[j] == 0 && graph.weight[i][j] < minWeight) {
            //替换minWeight(寻找已经访问过的结点和未访问过的结点间的权值最小的边)
            minWeight = graph.weight[i][j];
            h1 = i;
            h2 = j;
          }
        }
      }
      //找到一条边是最小
      System.out.println("边<" + graph.data[h1] + "," + graph.data[h2] + "> 权值:" + minWeight);
      //将当前这个结点标记为已经访问
      visited[h2] = 1;
      //minWeight 重新设置为最大值 10000
      minWeight = 10000;
    }

  }
}

class MGraph {
  int verxs; //表示图的节点个数
  char[] data;//存放结点数据
  int[][] weight; //存放边，就是我们的邻接矩阵

  public MGraph(int verxs) {
    this.verxs = verxs;
    data = new char[verxs];
    weight = new int[verxs][verxs];
  }
}

